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Detection and Discrimination of Internal Faults, External Faults and Inrush Current in Power Transformers using Real-Time Digital Simulator and Intelligent Methods
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Zahra Moravej *   , Sajad Bagheri , Gevork Gharehpetian |
| Faculty of Electrical and Computer Engineering, Semnan University, Semnan, Iran. , zmoravej@semnan.ac.ir |
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Abstract: (5349 Views) |
| Today, differential relays are used in order to protect power transformers against all kinds of faults and events. Despite advances in relay fabrication technology, the detection and discrimination of different events is still one of the most important challenges for the protection engineers in this field. In this paper, an intelligent hybrid method has been proposed to detect and classify internal electrical faults, external faults while saturating Current Transformers (CTs) and inrush current in transformers. First, the internal and external fault currents and the inrush currents of power transformers are simulated by the Real-Time Digital Simulator (RTDS) and its software package (RSCAD). Then, the sampled signals in different events are transmitted to MATLAB software for detection and discrimination. At this stage, using the Bayesian Classifier method, which directly evaluates the training data information, external faults are separated from the other operating conditions of the transformer. Then, other events such as inrush current and internal electrical faults will be distinguished from each other by Decision Tree (DT) and Support Vector Machine (SVM) methods. The results show that the proposed intelligent hybrid protection method has the ability to detect and classify different disturbances in transformers in real time state with appropriate accuracy, which is one of the main innovations of this study compared to other published research. |
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| Keywords: Differential Protection, RTDS/RSCAD, Bayesian Classifier, Decision Tree, Support Vector Machine |
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Full-Text [PDF 1086 kb]
(1529 Downloads)
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Type of Study: Research |
Subject:
Electrical Power Systems (Operation, Control, Analysis, ...)
Received: 2021/05/31 | Accepted: 2021/10/5 | Published: 2022/01/19
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